Wenyue Guo
Biographic Data
| ID | 9966064 |
|---|---|
| NAME | Wenyue Guo |
| GIVEN NAMES | Wenyue |
| FAMILY NAME | Guo |
| SIGNATURE | GUO W |
| AFFILIATIONS | PLA Information Engineering University |
| ORCID | 0000-0002-5538-7535 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Clinical features of Covid-19 infection in patients with myasthenia gravis
Objective We investigated the risk factors associated with severe or critical Coronavirus disease 2019 (COVID-19) infection due to the Omicron variant in patients with myasthenia gravis (MG) and determined the potential effect of COVID-19 on myasthenic exacerbation during the Omicron pandemic. Methods This retrospective study included 287 patients with MG in Tianjin, China. Clinical data of the patients were collected using electronic questionnai…
A Contour Line Group Simplification Method Based on Classified Terrain Features
Contour line group simplification methods can effectively preserve terrain features during map making and producing. This process involves two main steps, namely terrain feature line extraction and contour bend selection. The terrain feature line extraction includes two steps, that is, terrain feature point extraction and classification, and terrain feature line connection. However, to date, many similar studies have not considered the hierarchy …
Leveraging Deep Convolutional Neural Network for Point Symbol Recognition in Scanned Topographic Maps
Point symbols on a scanned topographic map (STM) provide crucial geographic information. However, point symbol recognition entails high complexity and uncertainty owing to the stickiness of map elements and singularity of symbol structures. Therefore, extracting point symbols from STMs is challenging. Currently, point symbol recognition is performed primarily through pattern recognition methods that have low accuracy and efficiency. To address th…
Predicting User Activity Intensity Using Geographic Interactions Based on Social Media Check-In Data
Predicting user activity intensity is crucial for various applications. However, existing studies have two main problems. First, as user activity intensity is nonstationary and nonlinear, traditional methods can hardly fit the nonlinear spatio-temporal relationships that characterize user mobility. Second, user movements between different areas are valuable, but have not been utilized for the construction of spatial relationships. Therefore, we p…
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Predicting User Activity Intensity Using Geographic Interactions Based on Social Media Check-In Data
Predicting user activity intensity is crucial for various applications. However, existing studies have two main problems. First, as user activity intensity is nonstationary and nonlinear, traditional methods can hardly fit the nonlinear spatio-temporal relationships that characterize user mobility. Second, user movements between different areas are valuable, but have not been utilized for the construction of spatial relationships. Therefore, we p…
A Contour Line Group Simplification Method Based on Classified Terrain Features
Contour line group simplification methods can effectively preserve terrain features during map making and producing. This process involves two main steps, namely terrain feature line extraction and contour bend selection. The terrain feature line extraction includes two steps, that is, terrain feature point extraction and classification, and terrain feature line connection. However, to date, many similar studies have not considered the hierarchy …
Leveraging Deep Convolutional Neural Network for Point Symbol Recognition in Scanned Topographic Maps
Point symbols on a scanned topographic map (STM) provide crucial geographic information. However, point symbol recognition entails high complexity and uncertainty owing to the stickiness of map elements and singularity of symbol structures. Therefore, extracting point symbols from STMs is challenging. Currently, point symbol recognition is performed primarily through pattern recognition methods that have low accuracy and efficiency. To address th…
Clinical features of Covid-19 infection in patients with myasthenia gravis
Objective We investigated the risk factors associated with severe or critical Coronavirus disease 2019 (COVID-19) infection due to the Omicron variant in patients with myasthenia gravis (MG) and determined the potential effect of COVID-19 on myasthenic exacerbation during the Omicron pandemic. Methods This retrospective study included 287 patients with MG in Tianjin, China. Clinical data of the patients were collected using electronic questionnai…
Artificial Intelligence (3 works) · Computer Science (3 works) · Mathematics (2 works) · 3D Surveying and Cultural Heritage (1 works) · Adrenal Hormones and Disorders (1 works) · Algorithm (1 works) · Automated Road and Building Extraction (1 works) · Cartography (1 works) · Computer vision (1 works) · Contour line (1 works)